Deep Learning with Keras and TensorFlow in R Workflow
1/27/20—1/28/20
9:00 AM-5:00 PM
2 Day Workshop
http://rstd.io/conf20-dl
Brad Boehmke
Data Scientist
84.51°
Overview
This two-day workshop introduces the essential concepts of building deep learning models with TensorFlow and Keras via R. First, we’ll establish a mental model of where deep learning fits in the spectrum of machine learning, highlight its benefits and limitations, and discuss how the TensorFlow - Keras - R toolchain work together. We'll then build an understanding of deep learning through first principles and practical applications covering a variety of tasks such as computer vision, natural language processing, anomaly detection, and more. Throughout the workshop you will gain an intuitive understanding of the architectures and engines that make up deep learning models, apply a variety of deep learning algorithms (i.e. MLPs, CNNs, RNNs, LSTMs, autoencoders), understand when and how to tune the various hyperparameters, and be able to interpret model results. Leaving this workshop, you should have a firm grasp of deep learning and be able to implement a systematic approach for producing high quality modeling results.
Is this workshop for you? If you answer "yes" to these three questions, then this workshop is likely a good fit:
- Are you relatively new to the field of deep learning and neural networks but eager to learn? Or maybe you have applied a basic feedforward neural network but aren't familiar with the other deep learning frameworks?
- Are you an experienced R user comfortable with the tidyverse, creating functions, and applying control (i.e. if, ifelse) and iteration (i.e. for, while) statements?
- Are you familiar with the machine learning process such as data splitting, feature engineering, resampling procedures (i.e. k-fold cross validation), hyperparameter tuning, and model validation? This workshop will provide some review of these topics but coming in with some exposure will help you stay focused on the deep learning details rather than the general modeling procedure details.
Prep work
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This is an applied workshop meaning we will be running lots of code so be sure to bring your
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We will be using an RStudio server on AWS. This means you do not need to worry about downloading certain packages or datasets ahead of time; everything will be prepared for you. Bonus - we get to play with GPUs
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All the content is open source. You can find the workshop repo at rstd.io/conf20-dl
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Please review the " Prework " section of the README so you are not surprised by the assumptions I make regarding prerequisite knowledge. Also, although you will be using an RStudio server with all the data and packages installed, I provide source code to install all prerequisites so that you can reproduce the analyses post-workshop on your own PC.
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Please review the "Setting up RStudio Cloud environment" instructions. I would highly suggest that you work through the instructions and actually log on prior to Monday morning. There are a few kinks still getting worked out so please don't run any notebooks but you should have no problems completing all the steps in the setup instructions. If you do have problems please let me know.
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This workshop is notebook focused, meaning we will be working through many R notebooks. If you are not familiar with R notebooks, take some time to review this: https://bookdown.org/yihui/rmarkdown/notebook.html .
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Feel free to poke around at some of the notebook material but understand that I am still putting some finishing touches on a few areas so you may notice slight changes between now and Monday. Consequently, if you want to clone/fork this repo I would either wait until we kick off the workshop or just plan on doing a git pull to update your content. If you don't know what clone/fork/pull means, don't worry
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Cheers 
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Brad
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